预测当天

stock/dnn_predict.py

@@ -6,10 +6,10 @@ from keras.layers import Dense,Dropout
 import random
 from keras.models import load_model
 
+lines = []
 def read_data(path):
-    lines = []
     with open(path) as f:
-        for line in f.readlines()[:1000]:
+        for line in f.readlines():
             lines.append(eval(line.strip()))
 
     size = len(lines[0])
@@ -17,16 +17,21 @@ def read_data(path):
     train_y=[s[size-1] for s in lines]
     return np.array(train_x),np.array(train_y)
 
-test_x,test_y=read_data("D:\\data\\quantization\\stock_test.log")
+# test_x,test_y=read_data("D:\\data\\quantization\\stock_test.log")
+test_x,test_y=read_data("D:\\data\\quantization\\s\\stock_2020-01-07.log")
 
 path="model_seq.h5"
 model=load_model(path)
-score = model.evaluate(test_x, test_y)
-print(score)
+# score = model.evaluate(test_x, test_y)
+# print(score)
 
 result=model.predict(test_x)
 # print(result)
 i = 0
-for x in test_y:
+for x in result:
     # print(str(i) + ":" + str(x))
+    if x[0] > 0.8:
+        print(lines[i][-2], x, 1)
+    # elif x[0] + x[1] > 0.9:
+    #     print(lines[i][-2], x, 2)
     i = i + 1